[FR] Plot recipe: ribbon plots option beside error bars about measurements.jl

[giordano]

Hi, thanks for the interest! I agree that having the ability to choose between a ribbon and error bars would be cool, but I have two concerns:

• does the ribbon make sense if you plot vectors? Or is it better to use it only for something smooth, like a function (plot(f, x))? Probably the distinction vectors vs function as input is moot, so maybe this concern is not too relevant, not sure
• you suggest to add a keyword argument (I don't like err very much though, a bit cryptic and confusing), but how does that work in practice? Does it compose with other keyword arguments defined by other recipes? I never explored this possibility, I really don't know how this works

If you can provide answers to these questions, I'd very much appreciate a pull request

[kapple19]

does the ribbon make sense if you plot vectors? Or is it better to use it only for something smooth, like a function (plot(f, x))? Probably the distinction vectors vs function as input is moot, so maybe this concern is not too relevant, not sure

I agree, it's better for a function.

I don't like err very much

Yeah me too, I can't think of a name.

Does it compose with other keyword arguments defined by other recipes?

Yes, it does! I did test this one out. It adds err (or whatever we might choose) to the optional arguments. I might test it a bit more to see how it behaves in different order, if it's better as a keyword argument, etc.

I'd very much appreciate a pull request

Okay cool. As I was writing this issue, I realised that I would need to do more experimenting and digging into the bigger picture of Measurements.jl and RecipesBase.jl to understand the best way to do this. I'll let you know once I've rigorously and thoroughly thought out some potential solution(s). Thanks @giordano!

[dfabianus]

Hello! :) Is there something new to this? I would use this quite often for model simulations where ribbons are way more effective than error bars.

My workaround right now is something like this:

y1 = Measurements.value.(y_meas)
y1u = Measurements.uncertainty.(y_meas)
# creating the ribbon
p = plot(t, y1.-y1u, fillranges = y1.+y1u, fillalpha = 0.25, linewidth=0, label = "" , fillcolor = 1)
# plotting the mean value on top
p = plot!(t, y1, label = "model", color=1)

[giordano]

Is there something new to this?

I already explained I don't know how to do this myself, if someone has a clear view of how to best implement this, they're welcome to submit a pull request. I don't think that has happened yet.