[DOCS] How to plot histogram uncertainties with weighted fills?

[APN-Pucky]

import numpy as np
import hist
hist1 = hist.Hist.new.Reg(50, 0, math.pi).Double()
hist1.fill(np.random.uniform(0, math.pi,200))
hist1.plot()

gives with (poisson) errorbars

while

import numpy as np
import hist
hist1 = hist.Hist.new.Reg(50, 0, math.pi).Double()
hist1.fill(np.random.uniform(0, math.pi,200),weight=np.random.uniform(0, math.pi,200))
hist1.plot()

gives none

I would have expected that it behaves like e.g. yoda that the weights squared produce the variance/uncertainty.

The docs https://hist.readthedocs.io/en/latest/reference/hist.plot.html#hist.plot.histplot say that I can give yerr, but yerr needs to be a vector of weights squared per bin. I don't think I should have to compute that myself, if I already filled the bins with the weights unsquared!
I could not find an example for this common case in the docs.
What is the recommended/right/best way to plot in hist with weights?

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Note: on the webpage there seems to be a small formatting error:

Histogram object with containing values and optionally bins. Can be:

is followed by bulletpoints, while

Histogram uncertainties. Following modes are supported:

does show dashes without newlines per case.

[APN-Pucky]

I guess I need to use .Weight() instead of .Double(), but that was not straightforward to find in the docs.