如何使用matplotlib在全息视图中绘制相同颜色的曲线和误差条？

Question

I want to plot a curve with error bars in holoviews using the matplotlib backend. I would like the curve and the error bars to be the same color, but without explicitly specifying the color for the curve. Ie I can easily do this

import holoviews as hv
hv.extension("matplotlib")

means = [1, 4, 2, 3]
errors = [0.3, 0.5, 0.2, 0.1]
color = "green"
mean_plot = hv.Curve(means).opts(color=color)
err_plot = hv.ErrorBars((range(len(means)), means, errors)).opts(edgecolor=color)
mean_plot * err_plot

to get

but what if I was given mean_plot and didn't already know its color? I'm sure the current options must be stored somewhere on the instance, but I don't know how to access them. I'd like to do something like

mean_color = mean_plot.<access_options_somehow>.color
err_plot = hv.ErrorBars((range(len(means)), means, errors)).opts(edgecolor=mean_color)

Answer 1

I do not have holoviews installed but since it is using matplotlib , you can try the generic solution to extract the color of the line and then use it to plot the error bars

mean_plot = hv.Curve(means) # Don't specify any color here
mean_color = mean_plot[0].get_color() # Extract the default color
err_plot = hv.ErrorBars((range(len(means)), means, errors)).opts(edgecolor=mean_color)

Answer 2

Based on @Sheldore's answer and my comment there, here's an approach that first renders the holoviews element to a matplotlib figure and then finds the color there. This isn't very elegant, and I think there must be a nicer way, but it gets the job done.

import holoviews as hv
hv.extension("matplotlib")

means = [1, 4, 2, 3]
errors = [0.3, 0.5, 0.2, 0.1]
color = "green"
mean_plot = hv.Curve(means).opts(color=color)

fig = hv.render(mean_plot)
ax = fig.axes[0]
line = ax.get_lines()[0]
mean_color = line.get_color()

err_plot = hv.ErrorBars((range(len(means)), means, errors)).opts(edgecolor=mean_color)
mean_plot * err_plot