Easy SOM

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-10-27

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Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Easy SOM plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:

https://hiplot.cn/basic/easy-som?lang=en

Establish the SOM model and conduct the visulization.

Setup

  • System Requirements: Cross-platform (Linux/MacOS/Windows)

  • Programming language: R

  • Dependent packages: data.table; jsonlite; kohonen

# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("kohonen", quietly = TRUE)) {
  install.packages("kohonen")
}

# Load packages
library(data.table)
library(jsonlite)
library(kohonen)
sessioninfo::session_info("attached")
─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.6.0 (2026-04-24)
 os       Ubuntu 24.04.4 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  C.UTF-8
 ctype    C.UTF-8
 tz       UTC
 date     2026-05-09
 pandoc   3.1.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.9.37 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package    * version date (UTC) lib source
 data.table * 1.18.4  2026-05-06 [1] RSPM
 jsonlite   * 2.0.0   2025-03-27 [1] RSPM
 kohonen    * 3.0.13  2026-01-22 [1] RSPM

 [1] /home/runner/work/_temp/Library
 [2] /opt/R/4.6.0/lib/R/site-library
 [3] /opt/R/4.6.0/lib/R/library
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

Data Preparation

# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/easy-som/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)

# convert data structure
target <- data[,1]
target <- factor(target, levels = unique(target))
data <- data[,-1]
data <- as.data.frame(data)
for (i in 1:ncol(data)) {
  data[,i] <- as.numeric(data[,i])
}
data <- as.matrix(data)
set.seed(7)
kohmap <- xyf(scale(data), target, grid = somgrid(xdim=6, ydim=4, topo="hexagonal"), rlen=100)

color_key <- c("#A50026","#D73027","#F46D43","#FDAE61","#FEE090","#FFFFBF","#E0F3F8",
               "#ABD9E9","#74ADD1","#4575B4","#313695")
colors <- function (n, alpha, rev = FALSE) {
  colorRampPalette(color_key)(n)
}

# View data
head(data[,1:5])
     alcohol malic acid  ash ash alkalinity magnesium
[1,]   12.86       1.35 2.32           18.0       122
[2,]   12.88       2.99 2.40           20.0       104
[3,]   12.81       2.31 2.40           24.0        98
[4,]   12.70       3.55 2.36           21.5       106
[5,]   12.51       1.24 2.25           17.5        85
[6,]   12.60       2.46 2.20           18.5        94

Visualization

# Easy SOM
p <- function () {
  par(mfrow = c(3,2))
  xyfpredictions <- classmat2classvec(getCodes(kohmap, 2))
  plot(kohmap, type="counts", col = as.integer(target),
       palette.name = colors,
       pchs = as.integer(target), 
       main = "Counts plot", shape = "straight", border = NA)
  
  som.hc <- cutree(hclust(object.distances(kohmap, "codes")), 3)
  add.cluster.boundaries(kohmap, som.hc)

  plot(kohmap, type="mapping",
       labels = as.integer(target), col = colors(3)[as.integer(target)],
       palette.name = colors,
       shape = "straight",
       main = "Mapping plot")

  ## add background colors to units according to their predicted class labels
  xyfpredictions <- classmat2classvec(getCodes(kohmap, 2))
  bgcols <- colors(3)
  plot(kohmap, type="mapping", col = as.integer(target),
       pchs = as.integer(target), bgcol = bgcols[as.integer(xyfpredictions)],
       main = "Another mapping plot", shape = "straight", border = NA)
  
  similarities <- plot(kohmap, type="quality", shape = "straight",
                       palette.name = colors)
  
  plot(kohmap, type="codes", shape = "straight", 
       main = c("Codes X", "Codes Y"), palette.name = colors)
}

p()
Figure 1: Easy SOM