A heatmap displaying values in a matrix format using color intensity. Each cell's color represents the magnitude of the value, making it easy to identify patterns, clusters, and outliers in two-dimensional data. Essential for visualizing correlations, frequencies, and relationships between variables.

# anyplot.ai
# heatmap-basic: Basic Heatmap
# Library: makie 0.22.10 | Julia 1.11.9
# Quality: 88/100 | Created: 2026-05-28
using CairoMakie
using Colors
using Random
using Statistics
using Printf
Random.seed!(42)
# Theme tokens
const THEME = get(ENV, "ANYPLOT_THEME", "light")
const PAGE_BG = THEME == "light" ? colorant"#FAF8F1" : colorant"#1A1A17"
const INK = THEME == "light" ? colorant"#1A1A17" : colorant"#F0EFE8"
const INK_SOFT = THEME == "light" ? colorant"#4A4A44" : colorant"#B8B7B0"
# Imprint diverging colormap (correlation data: meaningful midpoint at zero)
const _midpoint = THEME == "light" ? colorant"#FAF8F1" : colorant"#1A1A17"
const ANYPLOT_DIV = cgrad([colorant"#AE3030", _midpoint, colorant"#4467A3"])
# Data — climate variables, 200 daily observations
# Grouped by natural cluster for visual story:
# warm-moisture: Temp, Dewpoint, Humidity, Precip
# atmospheric: Wind, Pressure, Clouds, UV Index
var_labels = ["Temp", "Dewpoint", "Humidity", "Precip", "Wind", "Pressure", "Clouds", "UV Index"]
n = length(var_labels)
obs_raw = zeros(200, 8)
obs_raw[:, 1] = randn(200) # Temperature
obs_raw[:, 6] = 0.85 .* obs_raw[:, 1] .+ 0.53 .* randn(200) # Dewpoint ~ Temp
obs_raw[:, 2] = 0.45 .* obs_raw[:, 1] .+ 0.45 .* obs_raw[:, 6] .+ 0.45 .* randn(200) # Humidity
obs_raw[:, 5] = 0.55 .* obs_raw[:, 2] .+ 0.84 .* randn(200) # Precip ~ Humidity
obs_raw[:, 8] = 0.40 .* obs_raw[:, 5] .+ 0.92 .* randn(200) # Clouds ~ Precip
obs_raw[:, 7] = -0.55 .* obs_raw[:, 8] .+ 0.84 .* randn(200) # UV Index ~ -Clouds
obs_raw[:, 3] = 0.15 .* obs_raw[:, 1] .+ 0.99 .* randn(200) # Wind (mostly noise)
obs_raw[:, 4] = -0.25 .* obs_raw[:, 1] .+ 0.97 .* randn(200) # Pressure ~ -Temp
# Reorder: [Temp=1, Dewpoint=6, Humidity=2, Precip=5 | Wind=3, Pressure=4, Clouds=8, UV=7]
obs = obs_raw[:, [1, 6, 2, 5, 3, 4, 8, 7]]
corr_mat = cor(obs)
# Square canvas for symmetric heatmap
fig = Figure(
size = (1200, 1200),
fontsize = 14,
backgroundcolor = PAGE_BG,
)
ax = Axis(
fig[1, 1];
title = "heatmap-basic · julia · makie · anyplot.ai",
titlesize = 20,
titlecolor = INK,
subtitle = "Climate Variables · 200 Daily Observations",
subtitlesize = 13,
subtitlecolor = INK_SOFT,
xlabel = "",
ylabel = "",
xticklabelcolor = INK_SOFT,
yticklabelcolor = INK_SOFT,
xticksize = 0,
yticksize = 0,
backgroundcolor = PAGE_BG,
topspinevisible = false,
rightspinevisible = false,
leftspinevisible = false,
bottomspinevisible = false,
xgridvisible = false,
ygridvisible = false,
xticks = (1:n, var_labels),
yticks = (1:n, var_labels),
xticklabelrotation = π / 4,
xticklabelsize = 13,
yticklabelsize = 13,
yreversed = true,
)
hm = heatmap!(ax, 1:n, 1:n, corr_mat;
colormap = ANYPLOT_DIV,
colorrange = (-1.0, 1.0),
)
# Thin cell grid lines — delineate cells, especially near-zero in dark theme
cell_edges = [i + 0.5 for i in 0:n]
vlines!(ax, cell_edges; color = RGBAf(INK.r, INK.g, INK.b, 0.20), linewidth = 0.6)
hlines!(ax, cell_edges; color = RGBAf(INK.r, INK.g, INK.b, 0.20), linewidth = 0.6)
# Highlight warm-moisture cluster (top-left 4×4 block: Temp/Dewpoint/Humidity/Precip)
lines!(ax,
[0.5, 4.5, 4.5, 0.5, 0.5],
[0.5, 0.5, 4.5, 4.5, 0.5];
color = colorant"#009E73",
linewidth = 3.0,
)
# Cell value annotations — fontsize=13 for mobile readability on dense 64-cell grid
positions = Point2f[]
cell_labels = String[]
for i in 1:n, j in 1:n
push!(positions, Point2f(i, j))
push!(cell_labels, @sprintf("%.2f", corr_mat[i, j]))
end
text!(ax, positions; text = cell_labels, align = (:center, :center), color = INK, fontsize = 13)
# Colorbar
Colorbar(fig[1, 2], hm;
label = "Pearson r",
labelcolor = INK,
tickcolor = INK_SOFT,
ticklabelcolor = INK_SOFT,
ticklabelsize = 12,
labelsize = 13,
width = 22,
)
# Fine-tune gap between heatmap and colorbar
colgap!(fig.layout, 1, 12)
# Save
save("plot-$(THEME).png", fig; px_per_unit = 2)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/heatmap-basic/makie/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "heatmap-basic",
"language": "julia",
"library": "makie",
"page": "https://anyplot.ai/heatmap-basic/julia/makie",
"hub": "https://anyplot.ai/heatmap-basic",
"code_json": "https://api.anyplot.ai/specs/heatmap-basic/makie/code",
"spec_json": "https://api.anyplot.ai/specs/heatmap-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/heatmap-basic/julia/makie/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/heatmap-basic/julia/makie/plot-dark.png",
"quality_score": 88.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Basic Heatmap on anyplot.ai.