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hexbin ​

# Makie.hexbin — Function.
julia
hexbin(xs, ys; kwargs...)

Plots a heatmap with hexagonal bins for the observations xs and ys.

Plot type

The plot type alias for the hexbin function is Hexbin.

source


Examples ​

Setting the number of bins ​

Setting bins to an integer sets the number of bins to this value for both x and y. The minimum number of bins in one dimension is 2.

julia
using CairoMakie
using Random
Random.seed!(1234)

f = Figure(size = (800, 800))

x = rand(300)
y = rand(300)

for i in 2:5
    ax = Axis(f[fldmod1(i-1, 2)...], title = "bins = $i", aspect = DataAspect())
    hexbin!(ax, x, y, bins = i)
    wireframe!(ax, Rect2f(Point2f.(x, y)), color = :red)
    scatter!(ax, x, y, color = :red, markersize = 5)
end

f

You can also pass a tuple of integers to control x and y separately.

julia
using CairoMakie
using Random
Random.seed!(1234)

f = Figure(size = (800, 800))

x = rand(300)
y = rand(300)

for i in 2:5
    ax = Axis(f[fldmod1(i-1, 2)...], title = "bins = (3, $i)", aspect = DataAspect())
    hexbin!(ax, x, y, bins = (3, i))
    wireframe!(ax, Rect2f(Point2f.(x, y)), color = :red)
    scatter!(ax, x, y, color = :red, markersize = 5)
end

f

Setting the size of cells ​

You can also control the cell size directly by setting the cellsize keyword. In this case, the bins setting is ignored.

The height of a hexagon is larger than its width. This is why setting the same size for x and y will result in uneven hexagons.

julia
using CairoMakie
using Random
Random.seed!(1234)

f = Figure(size = (800, 800))

x = rand(300)
y = rand(300)

for (i, cellsize) in enumerate([0.1, 0.15, 0.2, 0.25])
    ax = Axis(f[fldmod1(i, 2)...], title = "cellsize = ($cellsize, $cellsize)", aspect = DataAspect())
    hexbin!(ax, x, y, cellsize = (cellsize, cellsize))
    wireframe!(ax, Rect2f(Point2f.(x, y)), color = :red)
    scatter!(ax, x, y, color = :red, markersize = 5)
end

f

To get evenly sized hexagons, set the cell size to a single number. This number defines the cell width, the height will be computed as 2 * step_x / sqrt(3). Note that the visual appearance of the hexagons will only be even if the x and y axis have the same scaling, which is why we use aspect = DataAspect() in these examples.

julia
using CairoMakie
using Random
Random.seed!(1234)

f = Figure(size = (800, 800))

x = rand(300)
y = rand(300)

for (i, cellsize) in enumerate([0.1, 0.15, 0.2, 0.25])
    ax = Axis(f[fldmod1(i, 2)...], title = "cellsize = $cellsize", aspect = DataAspect())
    hexbin!(ax, x, y, cellsize = cellsize)
    wireframe!(ax, Rect2f(Point2f.(x, y)), color = :red)
    scatter!(ax, x, y, color = :red, markersize = 5)
end

f

Hiding hexagons with low counts ​

All hexagons with a count lower than threshold will be removed:

julia
using CairoMakie
using Random
Random.seed!(1234)

f = Figure(size = (800, 800))

x = randn(100000)
y = randn(100000)

for (i, threshold) in enumerate([1, 10, 100, 500])
    ax = Axis(f[fldmod1(i, 2)...], title = "threshold = $threshold", aspect = DataAspect())
    hexbin!(ax, x, y, cellsize = 0.4, threshold = threshold)
end
f

Changing the scale of the number of observations in a bin ​

You can pass a scale function to via the colorscale keyword, which will be applied to the bin counts before plotting.

julia
using CairoMakie
using Random
Random.seed!(1234)

x = randn(100000)
y = randn(100000)

f = Figure()
hexbin(f[1, 1], x, y, bins = 40,
    axis = (aspect = DataAspect(), title = "colorscale = identity"))
hexbin(f[1, 2], x, y, bins = 40, colorscale=log10,
    axis = (aspect = DataAspect(), title = "colorscale = log10"))
f

Showing zero count hexagons ​

By setting threshold = 0, all hexagons that fit into the limits of the input data are shown. In this example, we add a transparent color to the start of the colormap and stroke each hexagon so the empty hexagons are visible but not too distracting.

julia
using CairoMakie
using DelimitedFiles


a = map(Point2f, eachrow(readdlm(assetpath("airportlocations.csv"))))

f, ax, hb = hexbin(a,
    cellsize = 6,
    axis = (; aspect = DataAspect()),
    threshold = 0,
    colormap = [Makie.to_color(:transparent); Makie.to_colormap(:viridis)],
    strokewidth = 0.5,
    strokecolor = :gray50,
    colorscale = Makie.pseudolog10)

tightlimits!(ax)

Colorbar(f[1, 2], hb,
    label = "Number of airports",
    height = Relative(0.5)
)
f

Applying weights to observations ​

julia
using CairoMakie

using Random
Random.seed!(1234)

f = Figure(size = (800, 800))

x = 1:100
y = 1:100
points = vec(Point2f.(x, y'))

weights = [nothing, rand(length(points)), Makie.StatsBase.eweights(length(points), 0.005), Makie.StatsBase.weights(randn(length(points)))]
weight_labels = ["No weights", "Vector{<: Real}", "Exponential weights (StatsBase.eweights)", "StatesBase.weights(randn(...))"]

for (i, (weight, title)) in enumerate(zip(weights, weight_labels))
    ax = Axis(f[fldmod1(i, 2)...], title = title, aspect = DataAspect())
    hexbin!(ax, points; weights = weight)
    autolimits!(ax)
end

f

Attributes ​

alpha ​

Defaults to 1.0

The alpha value of the colormap or color attribute. Multiple alphas like in plot(alpha=0.2, color=(:red, 0.5), will get multiplied.

bins ​

Defaults to 20

If an Int, sets the number of bins in x and y direction. If a Tuple{Int, Int}, sets the number of bins for x and y separately.

cellsize ​

Defaults to nothing

If a Real, makes equally-sided hexagons with width cellsize. If a Tuple{Real, Real} specifies hexagon width and height separately.

colormap ​

Defaults to @inherit colormap :viridis

Sets the colormap that is sampled for numeric colors. PlotUtils.cgrad(...), Makie.Reverse(any_colormap) can be used as well, or any symbol from ColorBrewer or PlotUtils. To see all available color gradients, you can call Makie.available_gradients().

colorrange ​

Defaults to automatic

The values representing the start and end points of colormap.

colorscale ​

Defaults to identity

The color transform function. Can be any function, but only works well together with Colorbar for identity, log, log2, log10, sqrt, logit, Makie.pseudolog10 and Makie.Symlog10.

highclip ​

Defaults to automatic

The color for any value above the colorrange.

lowclip ​

Defaults to automatic

The color for any value below the colorrange.

nan_color ​

Defaults to :transparent

The color for NaN values.

strokecolor ​

Defaults to :black

No docs available.

strokewidth ​

Defaults to 0

No docs available.

threshold ​

Defaults to 1

The minimal number of observations in the bin to be shown. If 0, all zero-count hexagons fitting into the data limits will be shown.

weights ​

Defaults to nothing

Weights for each observation. Can be nothing (each observation carries weight 1) or any AbstractVector{<: Real} or StatsBase.AbstractWeights.