Elan Ernest

If the `clip_on` argument is set to `True`, plt.annotate(xy=(3, 3), s='test', clip_on=True) the output is as expected. A confusing bit is that the annotations have a `annotation_clip` argument in addition...

No, it's not an issue of the correct defaults. The issue is that `annotation_clip` is considered only for finding out whether or not to *draw* the annotation, but not for...

Due to the drawbacks of both possible solutions to this, I don't think this will be solved anytime soon. Also, one may consider it as a documentation issue, clarifying the...

Yes, but you can easily get the annotation to show up using plt.annotate(xy=(3, 3), s='test', annotation_clip=False) So the question is, whether it's worth putting in a hacky solution with some...

The point is, you *do* want to show the annotations outside the axes in cases the anchor point is in data coordinates and still inside the axes, or in cases...

In #15096 @jklymak asked > Is there any use to annotation_clip and clip_on to ever be different? As answer, here are all combinations: 

I'm not sure. Maybe in cases where you don't have any arrow? What's the alternative, though? Giving `clip_on` a third state `None` that is only used by annotations? But that...

The image is clipped by the axes. You will see it if you make your canvas squared and remove any margins. ``` from numpy import random import matplotlib.pyplot as plt...

The confusion is absolutely understandable. This is a semantic pitfall, unfortunately anchored deeply inside matplotlib. On the one hand, `argument=None` is mostly interpreted as "use the default", e.g. * `imshow(...,...

The [transforms tutorial](https://matplotlib.org/tutorials/advanced/transforms_tutorial.html) is pretty clear that `None` is the same as the Identity.  It also says > it is most common for artists placed in an axes or...