python - Warning " Adding an axes using the same arguments" and custom plot function

Question

I have made a function that makes histograms plot the way I like it (with error bars!).

def histoPlot(h,fmt='.',lighter_error=0.75,**kwargs):
#fig, ax = plt.subplots(1)
ax = plt.axes()
# Get the current color in the cycle     #https://stackoverflow.com/questions/28779559/how-to-set-same-color-for-markers-and-lines-in-a-matplotlib-plot-loop

color = next(ax._get_lines.prop_cycler)['color']
if all(h.uncertainties != None):
    # plot the error bar https://matplotlib.org/gallery/statistics/errorbar_features.html?highlight=error%20plot
    ax.errorbar(u.midpoints(h.bins), h.counts, yerr=h.uncertainties,color = lighten_color(color,lighter_error),fmt=fmt )
# plot the histogram
ax.step(h.bins,np.append(h.counts,h.counts[-1:]),where='post',color=color,**kwargs)

This is perfect for me now, I can use it to make a complex plot in a simple line

histoPlot(histo1,fmt=',')

I can also stack one plot upon the other by putting two lines in the same cell

histoPlot(histo1,fmt=',')`
histoPlot(histo2,fmt=',')

but I get a warning

MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
  warnings.warn(message, mplDeprecation, stacklevel=1)

I have been able to send away the warning (following Matplotlib: Adding an axes using the same arguments as a previous axes), but only at the price of making my function fail to be stackable. That is to say that each call of the function makes a new frame with a new plot. How can I get rid of this warning and still be able to stack my plots?

标签： pythonmatplotlib

Answer 1

每次在函数内部使用ax = plt.axes(). 如果要在同一图中绘制所有直方图，则必须传递该特定轴对象。以下是解释此问题的示例答案

import matplotlib.pyplot as plt
import numpy as np; np.random.seed(121)

fig, ax = plt.subplots()

def histoPlot(ax):
    ax.hist(np.random.normal(0, 1, 1000), bins=100)

histoPlot(ax)
histoPlot(ax)
histoPlot(ax)
plt.show()