When working with Julia, you may come across situations where you want to disable the plot pane. This can be useful when you are running code that generates a large number of plots and you don’t want to clutter your workspace with unnecessary plots. In this article, we will explore three different ways to disable the plot pane in Julia.
Option 1: Using the PyPlot package
The PyPlot package is a popular plotting library in Julia that provides a MATLAB-like interface for creating plots. To disable the plot pane using PyPlot, you can use the following code:
using PyPlot
pygui(false)
This code imports the PyPlot package and then sets the pygui variable to false, which disables the plot pane. Now, when you generate plots using PyPlot, they will not be displayed in the plot pane.
Option 2: Using the Plots package
The Plots package is another popular plotting library in Julia that provides a high-level interface for creating plots. To disable the plot pane using Plots, you can use the following code:
using Plots
default(show = false)
This code imports the Plots package and then sets the default show option to false, which disables the plot pane. Now, when you generate plots using Plots, they will not be displayed in the plot pane.
Option 3: Using the Gadfly package
The Gadfly package is a plotting library in Julia that provides a grammar of graphics interface for creating plots. To disable the plot pane using Gadfly, you can use the following code:
using Gadfly
set_default_plot_size(0cm, 0cm)
This code imports the Gadfly package and then sets the default plot size to 0cm, effectively disabling the plot pane. Now, when you generate plots using Gadfly, they will not be displayed in the plot pane.
Out of the three options, the best one depends on your specific needs and preferences. If you are already using PyPlot, Option 1 is a good choice. If you prefer a high-level interface, Option 2 with the Plots package is a great option. If you are using Gadfly or prefer a grammar of graphics interface, Option 3 is the way to go. Ultimately, it is up to you to decide which option works best for your workflow.
