Error bars in px.scatter should inherit color and opacity from markers by default

Error bars do correctly show with the same color (not opacity) as markers when using categorical data to set the color parameter:

import plotly.express as px
df = px.data.iris()
df["e_plus"] = df["sepal_width"]/100
df["e_minus"] = df["sepal_width"]/40
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
                 error_y="e_plus", error_y_minus="e_minus")

fig.show()

However, setting the opacity parameter only changes the opacity of the markers:

fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
                 error_y="e_plus", error_y_minus="e_minus", opacity=0.6)

fig.show()

And using numerical data to set the color parameter, the error bars will not have the same color as the markers, but instead renders in black:

fig = px.scatter(df, x="sepal_width", y="sepal_length", color="petal_width",
                 error_y="e_plus", error_y_minus="e_minus")

fig.show()

Fixing this would be super helpful, since the only current solution seems to be to manually add or update the trace for every single data point to set rgba-values for the error bars. My scatter plot had a few thousand data points, making that a very time consuming for-loop.

Start with the provided px.scatter reproductions using categorical and numerical color values, with and without opacity. Inspect the generated error-bar and marker settings to identify where their color and opacity diverge. Done means error bars inherit the marker color and opacity by default in all shown cases, with coverage for the reproductions.