FigureWidget update issues after single bin histogram.

Running into an (admittedly quite edgy) issue updating a plotly graph_object Histogram in a FigureWidget.

The issue only seems to arise when using barmode='overlay' and seems to result from updating .data[0].x to a degenerative
(single bin) array (i.e. all elements equal).

Running in Jupyterlab the issue can be reproduced by:

import plotly.graph_objects as go
import numpy as np
hist_wgt = go.FigureWidget([go.Histogram(x=np.random.random(200), histnorm='probability', opacity=0.7)],
                          layout=dict(barmode='overlay'))
display(hist_wgt)

which produces a nicely binned histogram e.g.

and

print("xrange:", hist_wgt.layout.xaxis.range)
print("nbinsx:", hist_wgt.data[0].nbinsx)
print("yrange:",hist_wgt.layout.yaxis.range)
print("start:", hist_wgt.data[0].xbins.start)
print("end:", hist_wgt.data[0].xbins.end)
print("size:", hist_wgt.data[0].xbins.size)

xrange: (6.938893903907228e-17, 0.9999999999999999)
nbinsx: 0
yrange: (0, 0.1736842105263158)
start: 0
end: 1
size: 0.1

However, if we update hist_wgt.data[0].x with a (terrible) uniform array:

hist_wgt.data[0].x = np.ones(200)

the histogram becomes a single bin (as expected):

and the layout and bin info:

xrange: (0.5, 1.5)
nbinsx: 0
yrange: (0, 1.0526315789473684)
start: 0.5
end: 1.5
size: 1

The issue now happens when we try to update hist_wgt.data[0].x, but with with a more sensible array:

hist_wgt.data[0].x = np.random.random(200) * 1e6

it seems the widget layout is not re-evaluated or updated for this new x:

although nbinsx does get set to None (unsure if this is significant):

xrange: (0.5, 1.5)
nbinsx: None
yrange: (0, 1.0526315789473684)
start: 0.5
end: 1.5
size: 1

My guess is that the ambiguous nature of bin-width where the data range is 0 means that something is being set for the widget layout for that special case -- and then this setting overrides any later auto-range operations?

I am happy to admit that trying to plot a single bin histogram is slightly pointless but I want the histogram to be updatable for user selected variables, some of which could could collapse to a single value. I have tried to find an option to force the layout update through but haven't stumble upon the right combination of calls.

まず JupyterLab で FigureWidget と go.Histogram の再現から始め、異なるデータから単一ビンの配列へ、そして元に戻る更新シーケンスを確認します。FigureWidget.data[0].x の変更によってヒストグラムのビンメタデータと軸範囲がどのように更新されるかを追跡します。新しいデータに対してレイアウトとビン情報が再計算され、単一ビンの値が保持されなければ完了です。