create_projection_plots: Create Projection Visualization Plots

In VoronoiBiomedPlot: Projection Visualization Plots for Dimensionally Reduced Data

Create Projection Visualization Plots

Description

Creates three types of visualization plots for 2D projected data: ellipse plots, Voronoi diagram plots, and combined ellipse-Voronoi plots. The function is designed to visualize class separation in dimensionally reduced data.

Usage

create_projection_plots(
  data,
  class_column = NULL,
  alternative_class_column = NULL,
  coordinate_columns = NULL,
  case_labels = NULL,
  coord_names = c("Dim1", "Dim2"),
  title = NULL,
  show_labels = FALSE,
  ellipse_alpha = 0.1,
  voronoi_alpha = 0.3,
  point_size = 2,
  legend_position = "bottom",
  color_palette = NULL,
  add_grid_lines = FALSE,
  color_points = "primary",
  fill_voronoi = "primary",
  point_shape = "none",
  label_fontface = "plain",
  label_size = 3.88
)

Arguments

data	A data frame containing projected data. Must have at least 2 numeric columns. If more than 2 columns are provided, the first 2 are used as coordinates.
class_column	Character string specifying the column name containing class labels, or a vector of class labels. If NULL, all observations are treated as a single class. Default: NULL.
alternative_class_column	Character string specifying the column name containing alternative class labels, or a vector of alternative class labels. If NULL, uses class_column. Default: NULL.
coordinate_columns	Character vector of length 2 specifying the column names to use as coordinates. If NULL, uses the first two numeric columns. Default: NULL.
case_labels	Character vector of case labels for individual observations. If NULL, row numbers are used. Default: NULL.
coord_names	Character vector of length 2 specifying names for the coordinate axes. Default: c("Dim1", "Dim2").
title	Character string for plot title. If NULL, no title is added. Default: NULL.
show_labels	Logical indicating whether to show case labels on plots. Default: FALSE.
ellipse_alpha	Numeric value (0-1) for ellipse transparency. Default: 0.1.
voronoi_alpha	Numeric value (0-1) for Voronoi polygon transparency. Default: 0.3.
point_size	Numeric value for point size. Default: 2.
legend_position	Character string or numeric vector specifying legend position. Default: "bottom".
color_palette	Function or character vector for color palette. If NULL, uses ggplot2 default colors. Default: NULL.
add_grid_lines	Logical indicating whether to add dashed grid lines at origin. Default: FALSE.
color_points	Character string specifying which classification to use for point colors. Either "primary" (uses class_column) or "alternative" (uses alternative_class_column). Default: "primary".
fill_voronoi	Character string specifying which classification to use for Voronoi fill. Either "primary" (uses class_column) or "alternative" (uses alternative_class_column). Default: "primary".
point_shape	Character string specifying which classification to use for point shapes. Either "primary" (uses class_column), "alternative" (uses alternative_class_column), or "none" (no shape differentiation). Default: "none".
label_fontface	Character string specifying the font face for text labels. Options include "plain", "bold", "italic", "bold.italic". Default: "plain".
label_size	Numeric value specifying the size of text labels. Default: 3.88.

Details

The function creates visualizations for 2D projected data, particularly useful for displaying results from dimensionality reduction techniques like PCA, PLS-DA, or t-SNE.

Voronoi tessellation divides the plot space into regions based on proximity to data points, providing an intuitive visualization of class boundaries and decision regions.

Confidence ellipses show the distribution spread and correlation structure within each class.

Value

A list containing three ggplot objects:

ellipse_plot	Plot with confidence ellipses for each class
voronoi_plot	Plot with Voronoi tessellation regions
voronoi_plot_plus_ellipse	Combined plot with both Voronoi regions and ellipses

Examples

# Basic usage with iris dataset
data <- iris[, c("Sepal.Length", "Petal.Length", "Species")]
plots <- create_projection_plots(
  data = data,
  class_column = "Species",
  legend_position = "bottom",
  add_grid_lines = FALSE
)

VoronoiBiomedPlot documentation built on Aug. 11, 2025, 1:07 a.m.