When working with Julia and generating plots, it is important to have clean and scientific formatting for the output. This ensures that the plots are visually appealing and easy to interpret. In this article, we will explore three different ways to achieve clean scientific formatting in Julia using the Plots.jl package.
Option 1: Using the Plots.jl default settings
The Plots.jl package provides default settings that can be used to achieve clean scientific formatting. By default, Plots.jl uses the GR backend, which is a high-performance plotting engine. To enable clean scientific formatting, we can simply set the default backend to GR and adjust the formatting options.
using Plots
gr()
With the above code, we set the default backend to GR. Now, let’s adjust the formatting options to achieve clean scientific formatting.
default(fmt = :svg)
default(size = (800, 600))
default(fontfamily = "Arial")
In the above code, we set the default output format to SVG, which is a vector-based format suitable for scientific plots. We also set the default size of the plots to 800×600 pixels and the default font family to Arial.
Option 2: Customizing the Plots.jl settings
If the default settings of Plots.jl do not meet your requirements, you can customize the settings to achieve clean scientific formatting. Plots.jl provides a wide range of options that can be adjusted to customize the appearance of the plots.
using Plots
gr()
Similar to Option 1, we set the default backend to GR. Now, let’s customize the formatting options to achieve clean scientific formatting.
default(fmt = :png)
default(size = (800, 600))
default(fontfamily = "Helvetica")
default(linewidth = 2)
default(color = :black)
In the above code, we set the default output format to PNG, which is a raster-based format suitable for scientific plots. We also set the default size of the plots to 800×600 pixels, the default font family to Helvetica, the default line width to 2, and the default color to black.
Option 3: Using the PyPlot backend
If neither the default settings nor the customized settings of Plots.jl meet your requirements, you can switch to the PyPlot backend, which provides more flexibility in terms of formatting options. PyPlot is a Julia interface to the popular Python plotting library, Matplotlib.
using Plots
pyplot()
With the above code, we switch the backend to PyPlot. Now, let’s customize the formatting options using the PyPlot backend.
default(fmt = :pdf)
default(size = (800, 600))
default(fontfamily = "Times New Roman")
default(linewidth = 1)
default(color = :blue)
In the above code, we set the default output format to PDF, which is a vector-based format suitable for scientific plots. We also set the default size of the plots to 800×600 pixels, the default font family to Times New Roman, the default line width to 1, and the default color to blue.
After exploring the three options, it is difficult to determine which one is better as it depends on the specific requirements of the plot and personal preferences. Option 1 provides a simple and straightforward way to achieve clean scientific formatting using the default settings of Plots.jl. Option 2 allows for more customization by adjusting the formatting options. Option 3 provides the most flexibility by switching to the PyPlot backend. It is recommended to experiment with different options and choose the one that best suits your needs.
