Philipp Rudiger
Philipp Rudiger
``` hv.RGB((da / (2**2)).clip(0, 255).astype(np.uint8).data.transpose([1, 2, 0])).opts(width=600) ``` 
Okay, I've come around I'd be okay with a two-pronged approach, we implement the robust semantics in hvPlot and then HoloViews appropriately clips the data.
>Taking the initial example, we can see the object returned is not a HoloViews element but a Panel object: This was an exceptionally bad decision on my part and should...
Returning a Panel objects; eventually we do want to accepts reactive references and then apply them with `.apply.opts()`.
Okay, finally sat down and made a start on continuous bar charts: https://github.com/holoviz/holoviews/pull/6145
This all sounds incredibly frustrating. I'm taking another deep look at this today, if someone has a reproducible way to trigger these issues I'd be very grateful.
Agree with @maximlt, the solution is not to allow a user to back out of some nonsensical selection that will, at best, cause lengthy processing in Python or at worst...
Very doubtful that threading hvPlot would meaningfully unlock the GIL.
>I'm a bit confused, HoloViews already has some support for datashader inspections? I see inspect_points and inspect_polygons in its code base at least. These are **very** crude implementations and cover...
>In which case, in the second notebook, the plot isn't rendered at all. @philippjfr do you happen to know if that is a fundamental limitation of Bokeh in JupyterLab, i.e....