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  • in Code
  • 1 min read

Force display format to PNG

In the VSCode plot panel and fredrikekre/Literate.jl notebooks, PNG images are generally smaller than SVG ones. To force plots to be shown as PNG images, you can use tkf/DisplayAs.jl to show objects in a chosen MIME type.

import DisplayAs.PNG
using Plots
plot(rand(6)) |> PNG

If you don't want to install another package, you could directly use display().

using Plots
PNG(img) = display("image/png", img)
plot(rand(6)) |> PNG
  • in Code
  • 1 min read

Get the ODE Function from an ODE system

f = ODEFunction(sys) could be useful in plotting vector fields.

using ModelingToolkit
using DifferentialEquations

# Independent (time) and dependent (state) variables (x and RHS)
@independent_variables t
@variables x(t) RHS(t)

# Setting parameters in the modeling
@parameters τ

# Differential operator w.r.t. time
D = Differential(t)

# Equations in MTK use the tilde character (`~`) as equality.
# Every MTK system requires a name. The `@named` macro simply ensures that the symbolic name matches the name in the REPL.

@mtkbuild sys = ODESystem([
    RHS  ~ (1 - x)/τ,
    D(x) ~ RHS
])

tend = 2.0
prob = ODEProblem(sys, [x=>0.0], tend, [τ=>1.0])

prob.f([0.0], prob.p, 0.0) # f(u, p, t) returns the value of D(x)
  • in Code
  • 3 min read

Plots.jl Tips

Some tips about Plots.jl, the de-facto standard visualization library in Julia.

You don't have to precalculate

Plots.jl supports tracing functions.

  • plot(f, tmin, tmax) or plot(f, tArray)
  • plot(fx, fy, tmin, tmax) or plot(fx, fy, tArray)

For example, you can easily draw a parametric plot for x(t) and y(t).

# plotting (x(t), y(t))
plot(sin, (x-> sin(2x)), 0, 2π, line = 4, leg = false)

Or make a contour plot without precalculating the function values

x = 1:0.5:20
y = 1:0.5:10

g(x, y) = (3x + y ^ 2) * abs(sin(x) + cos(y))

# Precalculate the value
X = repeat(reshape(x, 1, :), length(y), 1)
Y = repeat(y, 1, length(x))
Z = map(g, X, Y)

p2 = contour(x, y, Z)

# Generate z value on-the-fly

p1 = contour(x, y, g, fill=true)
plot(p1, p2)

Subplots

You can combine multiple plots into one single plot with a @layout.

l = @layout [a ; b c]
p1 = plot(...)
p2 = plot(...)
p3 = plot(...)

plot(p1, p2, p3, layout = l)

Or use the sp keyword argument

plot(layout=(2,2))

plot!(randn(50), sp=1)
plot!(randn(50), sp=2)
plot!(randn(50), sp=3)
plot!(randn(50), sp=4)

See layouts for more options.

List supported styles

# tip: use Plots.supported_styles() or Plots.supported_markers() to see which line styles or marker shapes you can use
@show Plots.supported_styles();
@show Plots.supported_markers();

See plot attributes.

Render Images

# using Pkg; Pkg.add("Images")

using Images
img1 = load("dog.jpg")
plot(img1)

LaTeX texts

Plots.jl supports LaTeX texts in the figure.

# using Pkg; Pkg.add("LaTeXStrings")
using LaTeXStrings
str = L"\textrm{Count}"

PDF output

  • PDF uses vector graphic format and conserves details.
  • Set figure size e.g. size=(750,750) to determine the relative fonts sizes.
  • One can convert PDF to tiff images later using pdftoppm or imagemagick.

Shared Color bar

Source. The trick is to
- make an blank scatter plot for the colorbar.
- use a dedicated space in the layout for the colorbar.

using Plots

x1 = range(0.0, 1.0, length=51)
y1 = range(-1.0, 0.0, length=51)
z1 = sin.(4*pi.*x1)*cos.(6*pi.*reshape(y1, 1, :))

x2 = range(0.25, 1.25, length=51)
y2 = range(-1.0, 0.0, length=51)
z2 = 2.0.*sin.(4*pi.*x2)*cos.(6*pi.*reshape(y2, 1, :))

x3 = range(0.0, 1.0, length=51)
y3 = range(-1.25, -0.25, length=51)
z3 = 3.0*sin.(4*pi.*x3)*cos.(6*pi.*reshape(y3, 1, :))

x4 = range(0.25, 1.25, length=51)
y4 = range(-1.25, -0.25, length=51)
z4 = 4.0.*sin.(4*pi.*x4)*cos.(6*pi.*reshape(y4, 1, :))

clims = extrema([z1; z2; z3; z4])

p1 = contourf(x1, y1, z1, clims=clims, c=:viridis, colorbar=false)
p2 = contourf(x2, y2, z2, clims=clims, c=:viridis, colorbar=false)
p3 = contourf(x3, y3, z3, clims=clims, c=:viridis, colorbar=false)
p4 = contourf(x4, y4, z4, clims=clims, c=:viridis, colorbar=false)

h2 = scatter([0,0], [0,1], zcolor=[0,3], clims=clims,
                xlims=(1,1.1), label="", c=:viridis,
                colorbar_title="cbar", framestyle=:none)

l = @layout [grid(2, 2) a{0.035w}]

p_all = plot(p1, p2, p3, p4, h2, layout=l, link=:all)