自定义热图

作者

[编辑] 郑虎;

[审核] .

修改于

2026-01-17

注记

Hiplot 网站

本页面为 Hiplot Custom Heatmap 插件的源码版本教程，您也可以使用 Hiplot 网站实现无代码绘图，更多信息请查看以下链接:

https://hiplot.cn/basic/custom-heat-map?lang=zh_cn

自定义热图，按照给定数据直接绘制热图。

环境配置

  • 系统: Cross-platform (Linux/MacOS/Windows)

  • 编程语言: R

  • 依赖包: data.table; jsonlite; ggplot2

# 安装包
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
  install.packages("ggplot2")
}

# 加载包
library(data.table)
library(jsonlite)
library(ggplot2)
sessioninfo::session_info("attached")
─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.5.2 (2025-10-31)
 os       Ubuntu 24.04.3 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  C.UTF-8
 ctype    C.UTF-8
 tz       UTC
 date     2026-01-18
 pandoc   3.1.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.8.27 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package    * version date (UTC) lib source
 data.table * 1.18.0  2025-12-24 [1] RSPM
 ggplot2    * 4.0.1   2025-11-14 [1] RSPM
 jsonlite   * 2.0.0   2025-03-27 [1] RSPM

 [1] /home/runner/work/_temp/Library
 [2] /opt/R/4.5.2/lib/R/site-library
 [3] /opt/R/4.5.2/lib/R/library
 * ── Packages attached to the search path.

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

数据准备

案例数据为hiplot.org官方logo的灰度图像。

# 加载数据
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/custom-heat-map/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)

# 整理数据格式
draw_data <- as.matrix(data[, 2:ncol(data)])
row_num <- nrow(draw_data)
col_num <- ncol(draw_data)
col_labels <- colnames(data)
col_labels <- col_labels[2:ncol(data)]
row_labels <- data$name
rm(data)
df <- expand.grid(row = 1:row_num, col = 1:col_num)
df$value <- c(draw_data)

# 查看数据
head(df)
  row col value
1   1   1   236
2   2   1   236
3   3   1   236
4   4   1   236
5   5   1   236
6   6   1   236

可视化

# 自定义热图
p <- ggplot(df, aes(x = col, y = row, fill = value)) +
  geom_point(shape = 21, size = 8, aes(fill = value), color = "white") +
  scale_fill_gradient(low = "#DDDDDD", high = "#0000F5") +
  guides(fill = guide_colorbar(title = "Value")) +
  theme(
    panel.background = element_rect(fill = "white"),
    panel.grid = element_blank(),
    axis.text = element_text(size = 10),
    axis.ticks = element_blank(),
    axis.title = element_blank()
    ) +
  scale_x_continuous(breaks = 1:col_num, labels = col_labels, position = "top") +
  scale_y_reverse(breaks = 1:row_num, labels = row_labels, position = "left")

p
图 1: 自定义热图