Unexpected behavior when changing a figure axis range

[raphaeltimbo]

I have the following code:

import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go

df = pd.DataFrame(
    {'CRL':
     {103: '5',
      104: '4',
      819: '3'},
 'TRL':
     {103: '6',
      104: '4',
      819: '2'},
 'COD_EV':
     {103: 'EV-00182',
      104: 'EV-00183',
      819: 'EV-01196'}
    }
)
g = [97, 181, 89, 0.5]
y = [255, 255, 100, 0.5]
r = [250, 112, 112, 0.5]

img_rgb = np.array(
    [
        [g, g, g, g, g, g, g, g, g, g],
        [g, r, r, r, g, y, y, y, y, y],
        [g, r, r, r, g, y, y, y, y, y],
        [g, r, r, r, g, y, y, y, y, y],
        [g, r, r, r, g, g, y, y, y, y],
        [g, r, r, r, r, g, y, y, y, y],
        [g, r, r, r, r, g, g, y, y, y],
        [g, r, r, r, r, r, g, g, y, y],
        [g, r, r, r, r, r, r, g, y, y],
        [g, r, r, r, r, r, r, g, g, g],
    ],
    dtype=np.float,
)

fig = px.strip(df, x="CRL", y="TRL", color="COD_EV")
fig.update_layout(
    xaxis=dict(
        showgrid=False,
        range=(0.5, 9.5),
        tickvals=[1, 2, 3, 4, 5, 6, 7, 8, 9],
        constrain="domain",
        title="CRL",
    ),
    yaxis=dict(
        showgrid=False,
        range=(0.5, 9.5),
        tickvals=[1, 2, 3, 4, 5, 6, 7, 8, 9],
        constrain="domain",
        title="TRL",
    ),
)

fig.update_traces(marker=dict(size=7), selector=dict(type="box"))
fig.add_traces(go.Image(z=img_rgb, colormodel="rgba"))
fig.update_traces(hovertemplate=None, hoverinfo="skip", selector=dict(type="image"))

Which would produce the following figure with plotly 4.12.0:

Now with plotly 4.14.3 I am getting this plot:

[gvwilson]

Hi - we are trying to tidy up the stale issues and PRs in Plotly's public repositories so that we can focus on things that are still important to our community. Since this one has been sitting for several years, I'm going to close it; if it is still a concern, please add a comment letting us know what recent version of our software you've checked it with so that I can reopen it and add it to our backlog. Thanks for your help - @gvwilson