Custom plot methods using `ggplot2` in packages. Best practices?

I'm writing a package with plot methods for the classes defined in it. When designing these plot methods, I figured out I could use ggplot2 functions and have these plot methods to transform the objects suitably and return a ggplot object, so users could benefit from all the flexibility ggplot2 provides.

On the other hand, if the user doesn't want/know ggplot2 at all, just using the method should result in a decent visualization.

My questions are about what are the best practices in these situations:

  • Should I just import ggplot2 and have the user load it if/when he wants to modify the "standard" visualization produced in the method or add it to the Depends field? Note that visualization is not the main purpose.
  • This "standard" plot method requires modifying some of the scales (e.g. the standard color scale is not good for the problem), so I add appropriate scale layers in the function definition. The problem is: when the user overwrites these scales (and I really wanted ggplot's flexibility so they're able to do it if they want to), it throws a warning Scale for 'fill' is already present. Adding another scale for 'fill', which will replace the existing scale. that will surely confuse the user. Is there a way to get rid of this warning? Is there a better approach here?


plot(myclass) + scale_fill_brewer()