When working with Julia, you may come across the need to create rasterized 3D surface plots inside vectorized figures. This can be a challenging task, but there are several ways to achieve it. In this article, we will explore three different options to solve this problem.
Option 1: Using the Plots.jl Package
The Plots.jl package is a powerful tool for creating various types of plots in Julia. To create a rasterized 3D surface plot inside a vectorized figure, you can use the `plotly()` backend provided by Plots.jl. Here’s an example code snippet:
using Plots
plotly()
# Generate data for the surface plot
x = range(-5, stop=5, length=100)
y = range(-5, stop=5, length=100)
z = [exp(-(x[i]^2 + y[j]^2)) for i in 1:length(x), j in 1:length(y)]
# Create the surface plot
surface(x, y, z, color=:viridis, camera=(30, 30))
This code snippet generates a 3D surface plot using the `surface()` function provided by Plots.jl. The `color=:viridis` argument sets the color scheme for the plot, and the `camera=(30, 30)` argument adjusts the viewing angle. The resulting plot will be rasterized inside the vectorized figure.
Option 2: Using the PyPlot.jl Package
If you prefer to use the popular Matplotlib library in Python, you can achieve the same result by using the PyPlot.jl package in Julia. Here’s an example code snippet:
using PyPlot
# Generate data for the surface plot
x = range(-5, stop=5, length=100)
y = range(-5, stop=5, length=100)
z = [exp(-(x[i]^2 + y[j]^2)) for i in 1:length(x), j in 1:length(y)]
# Create the surface plot
fig = figure()
ax = fig.add_subplot(111, projection="3d")
ax.plot_surface(x, y, z, cmap="viridis")
# Save the figure as a vectorized PDF
savefig("surface_plot.pdf", format="pdf")
This code snippet uses the PyPlot.jl package to create a 3D surface plot. The `figure()` function creates a new figure, and the `add_subplot()` function adds a 3D subplot to the figure. The `plot_surface()` function is then used to generate the surface plot. Finally, the `savefig()` function saves the figure as a vectorized PDF file.
Option 3: Using the Makie.jl Package
The Makie.jl package is another powerful tool for creating interactive visualizations in Julia. To create a rasterized 3D surface plot inside a vectorized figure, you can use the `surface()` function provided by Makie.jl. Here’s an example code snippet:
using Makie
# Generate data for the surface plot
x = range(-5, stop=5, length=100)
y = range(-5, stop=5, length=100)
z = [exp(-(x[i]^2 + y[j]^2)) for i in 1:length(x), j in 1:length(y)]
# Create the surface plot
scene = Scene()
surface!(scene, x, y, z, colormap=:viridis)
# Save the scene as a vectorized SVG
save("surface_plot.svg", scene, background_color=:transparent)
This code snippet uses the Makie.jl package to create a 3D surface plot. The `Scene()` function creates a new scene, and the `surface!()` function adds a surface plot to the scene. The `colormap=:viridis` argument sets the color scheme for the plot. Finally, the `save()` function saves the scene as a vectorized SVG file.
After exploring these three options, it is clear that the Plots.jl package provides the most straightforward and concise solution for creating rasterized 3D surface plots inside vectorized figures in Julia. It offers a high-level interface and supports various backends, making it a versatile choice for plotting tasks. However, the choice ultimately depends on your specific requirements and preferences.
