ControlPlots
Introduction
This package provides the following features:
- simple plots can be created with the
plot()
function - an oscilloscope-like plot with multiple channels can be created
with the
plotx()
function - an XY plot can be created with the
plotxy()
function - pan and zoom are supported
- LaTeX can be used for the labels
- the parameters of the plot commands are stored in a struct and returned
- this struct can be displayed again or stored in a file and loaded, the labels etc can be edited and a new plot can be displayed or exported
Planned features
TODO
- add support for PythonPlot
- allow changing of the caption
- the
save()
function should allow storing a plot as jld2, pdf or png file - add bode plots
The goal of this package is to provide simple plots for control system developers and students.
Installation
Installation on Linux
On Linux
First, install matplotlib:
sudo apt install python3-matplotlib
If not done yet, create a project:
mkdir MyProject
cd MyProject
julia --project="."
and install ControlPlots
using Pkg
pkg"add ControlPlots"
Installation on Windows
On Windows
If not done yet, create a project:
mkdir MyProject
cd MyProject
julia --project="."
Install Python, matplotlib and ControlPlots
using Pkg
ENV["PYTHON"]=""
pkg"add ControlPlots"
Usage
Basic example
Launch Julia with julia --project
. Then execute:
using ControlPlots, LaTeXStrings
X = 0:0.1:2pi
Y = sin.(X)
p = plot(X, Y, xlabel=L"\alpha = [0..2\pi]", ylabel="sin", fig="basic")
A plot window like this should pop up:
The package LaTeXStrings
is only required if you want to use LaTeX for any of your labels like in the example above. You need to prefix LaTeX strings with the letter L
.
You can now close the plot window. You can re-display the plot by typing:
p
You can also save the plot under a name of your choice:
save("plot.jld2", p)
Now you restart Julia and load it with:
using ControlPlots
p = load("plot.jld2")
The plot is automatically displayed.
Multi-channel plot
using ControlPlots
T = 0:0.1:2pi
Y1 = sin.(T)
Y2 = cos.(T)
p = plotx(T, Y1, Y2; ylabels=["Y1", "Y2"], fig="dual")
XY-Plot
using ControlPlots
T = 0:0.05:2pi+0.1
X = sin.(T)
Y = cos.(3T)
p = plotxy(X, Y, xlabel="X", ylabel="Y", fig="xy")
n-in-one Plot
You can plot multiple time series in one plot, e.g. like this:
using ControlPlots
x = 1.5*ones(11)
y = 1:0.1:2
out = min.(x, y)
plot(1:11, [x, y, out]; labels=["input_a", "input_b", "output"],
fig="2-in-one")
Dual y-axis
using ControlPlots
T = 0:0.05:2pi+0.1
POS_Z = sin.(T)
VEL_Z = 5*cos.(T)
plot(T, POS_Z, VEL_Z; xlabel="time [s]",
ylabels=["pos_z [m]", "vel_z [m/s]"],
labels=["pos_z", "vel_z"], fig="dual_y-axis")
2D video
A video-like display of a particle system (points, connected by lines) can be created with the
function plot2d
. Example:
using ControlPlots
t = 0
x0 = 2.0
z0 = 0.0
for t in 0:0.1:5
global x0, z0
plot2d([[1,0,0], [x0,0,z0]], t; segments=1)
x0 += 0.1; z0 += 0.1
sleep(0.1)
end
When the function is called at t=0 the line, dot and text objects are created. Each time afterwords these objects are just moved/ updated. Therefore, the update is very fast and you can achieve a high frame rate. With 10 points you can achieve a framerate of 20 Hz or more, depending on the speed of your hardware.
Advanced usage
This library uses Matplotlib as backend, and you can change all settings of rcParams as you wish. Example: Using an already installed LaTeX installation for high-quality rendering of LaTeX labels and other text:
More beautiful LaTeX
rcParams = plt.PyDict(plt.matplotlib."rcParams")
rcParams["text.usetex"] = true
Just add this at the beginning of your script. You can change fonts, font sizes, colors etc.
More beautiful GUI
If you add the following line to your .bashrc
file or to the script you use to start Julia:
export MPLBACKEND=qt5agg
you get a more beautiful GUI. This does not work on every PC, therefore it is not the default.