When working with Julia and trying to create a surface plot using the Plots package, you may encounter an issue where the data is not displayed when hovering over the plot. This can be frustrating, especially if you need to analyze the data points on the plot. However, there are several ways to solve this problem and ensure that the data is shown when hovering over the surface plot.
Option 1: Using the GR Backend
One way to solve this issue is by using the GR backend instead of the default backend. The GR backend provides more advanced features and better interactivity, including the ability to display data when hovering over the plot.
using Plots
gr()
By calling the gr()
function before creating the surface plot, you will switch to the GR backend. This should enable the data to be displayed when hovering over the plot.
Option 2: Enabling Interactivity
Another option is to enable interactivity for the plot. By default, the Plots package disables interactivity for performance reasons. However, you can enable it by setting the interact
attribute to true
when creating the plot.
using Plots
plotlyjs()
By calling the plotlyjs()
function before creating the surface plot, you will enable interactivity. This should allow the data to be displayed when hovering over the plot.
Option 3: Using a Different Visualization Package
If the above options do not work for you, you can try using a different visualization package that provides better support for displaying data on hover. One such package is the Plotly package, which is known for its interactive and customizable plots.
using Plotly
By using the Plotly package instead of the Plots package, you can create surface plots that display data when hovering over them. Plotly provides a wide range of interactive features and customization options, making it a powerful choice for visualizing data in Julia.
After trying out these three options, it is clear that using the Plotly package is the best solution for displaying data on hover in a surface plot. Plotly offers the most advanced interactivity and customization options, allowing for a more immersive and informative data visualization experience.