How to Use Color Gradients in Julia Plots
Description
A color gradient is one of the two color schemes supported by Julia’s visualization package Plots.jl
(the other is palette), which is what we commonly refer to as gradation. Simply put, a type that implements gradation is ColorGradient
.
Gradients are used to draw charts such as heatmap()
, surface()
, contour()
. If you want to differentiate the colors of various graphs, use a palette instead of a gradient.
Code
Symbol
It can be used with cgrad(symbol)
. The default gradient is cgrad(:inferno)
, and the colors are as follows.
using Plots
cgrad(:inferno)
heatmap(reshape(1:25, (5, 5)))
Pre-defined palettes and gradients in Plots.jl
can be found in the official documentation (More diverse palettes and gradients can be found in the official documentation of the package ColorSchemes.jl
here).
In Python’s matplotlib, the default colormap for imshow
that resembles a gradient is :viridis
.
heatmap(reshape(1:25, (5, 5)), fillcolor = cgrad(:viridis))
Custom Definition
A palette can be defined directly with cgrad([start color, end color])
. To set the points of color transformation, input a vector containing values between $0$ and $1$ as an optional argument.
cgrad([:blue, :orange])
cgrad([:blue, :orange], [0.1, 0.9])
cgrad([:blue, :orange], [0.5, 0.50001])
Keywords
rev
Entering the keyword argument rev = true
will reverse the order.
cgrad(:darktest)
cgrad(:darktest, rev = true)
scale
The keyword scale
specifies the scale of the gradient. You can input :log
or :exp
.
cgrad(:rainbow)
cgrad(:rainbow, scale = :log)
cgrad(:rainbow, scale = :exp)
Environment
- OS: Windows11
- Version: Julia 1.9.4, Plots v1.39.0