Matplotlib with multiple zorder grids does not work with errors

Question

I am currently dealing with some strange matplotlib behavior when building multiple errors with different y axes in one subplot.

In this case, the grid corresponding to the second error diagram always overlaps the first error graph. With the options, zorderI managed to move another grid below the errors.

I would like both lattices to be below two errors. Does anyone know a solution to this, or is this a bug in matplotlib?

I am using Python 2.7.12 with matplotlib 1.5.1.

Minimum working example:

import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.colors as colors

# numbers of epochs
ttimes_means_list = [251.4, 153.3, 22.0, 202.1, 46.6]
ttimes_stddevs_list = [32.1, 35.1, 12.0, 84.9, 14.7]
# numbers of times
times_means_list = [5231, 3167, 860, 3932, 1244]
times_stddevs_list = [1381, 572, 253, 1445, 215]

labels = ['x1', 'x2', 'x3', 'x4', 'x5']
linewidth=3

xvalues = np.arange(0, len(times_means_list), 1)
xvalues_s = xvalues + 0.1

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twinx()
ax1.set_ylabel('Number')
ax1.xaxis.grid(False)
ax1.yaxis.grid(True, color='navy', linewidth=linewidth/2.0)
ax2.xaxis.grid(False)
ax1.set_zorder(0)
ax2.set_zorder(0)
ax2.yaxis.grid(True, color='darkorange', linewidth=linewidth/2.0)
ax2.set_ylabel('Time')
ax1.set_xticks(xvalues)
ax2.set_xticks(xvalues)
ax1.set_xticklabels(labels)
ax2.set_xticklabels(labels)
ax1.set_xlabel('x label')
errplot1 = ax1.errorbar(xvalues, ttimes_means_list, yerr=ttimes_stddevs_list,
        linestyle="None", elinewidth=linewidth, color='navy', label='Number',
        capthick=linewidth, zorder=10)
errplot2 = ax2.errorbar(xvalues_s, times_means_list, yerr=times_stddevs_list, 
        linestyle="None", elinewidth=linewidth, color='darkorange',
        label='Time', capthick=linewidth, zorder=10)
ax1.set_axisbelow(True)
ax2.set_axisbelow(True)
fig.legend((errplot1, errplot2), ('number', 'time'), 
        loc='upper right', numpoints=1)
plt.xlim(-0.5, len(times_means_list)-0.5)
plt.title('Some plot title')
plt.savefig('mwe_plot.pdf')
plt.clf()

Output graph (orange grid points overlap blue bars):

Answer 1

, "".

import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.colors as colors

# numbers of epochs
ttimes_means_list = [251.4, 153.3, 22.0, 202.1, 46.6]
ttimes_stddevs_list = [32.1, 35.1, 12.0, 84.9, 14.7]
# numbers of times
times_means_list = [5231, 3167, 860, 3932, 1244]
times_stddevs_list = [1381, 572, 253, 1445, 215]

labels = ['x1', 'x2', 'x3', 'x4', 'x5']
linewidth=3

xvalues = np.arange(0, len(times_means_list), 1)
xvalues_s = xvalues + 0.1

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twinx()
ax1.set_ylabel('Number')
ax1.xaxis.grid(False)
g1 = ax1.yaxis.grid(True, color='navy', linewidth=linewidth/2.0)
ax2.xaxis.grid(False)
ax1.set_zorder(0)
ax2.set_zorder(0)
g2 = ax2.yaxis.grid(True, color='darkorange', linewidth=linewidth/2.0)
ax2.set_ylabel('Time')
ax1.set_xticks(xvalues)
ax2.set_xticks(xvalues)
ax1.set_xticklabels(labels)
ax2.set_xticklabels(labels)
ax1.set_xlabel('x label')
ax1.errorbar(xvalues, ttimes_means_list, yerr=ttimes_stddevs_list,
        linestyle="None", elinewidth=1, color='navy', label='Number',
        capthick=1, zorder=10,)
errplot2 = ax2.errorbar(xvalues_s, times_means_list, yerr=times_stddevs_list, 
        linestyle="None", elinewidth=linewidth, color='darkorange',
        label='Time', capthick=linewidth, zorder=10)
ax1.set_axisbelow(True)
ax2.set_axisbelow(True)

# draw the 'navy' line again
ax3 = ax1.twinx()
ax3.yaxis.grid(False)
errplot1 = ax3.errorbar(xvalues, ttimes_means_list, yerr=ttimes_stddevs_list,
        linestyle="None", elinewidth=linewidth, color='navy', label='Number',
        capthick=linewidth, zorder=10)

fig.legend((errplot1, errplot2), ('number', 'time'), 
        loc='upper right', numpoints=1)
plt.xlim(-0.5, len(times_means_list)-0.5)
plt.title('Some plot title')
# plt.savefig('mwe_plot.pdf')
# plt.clf()

plt.show()

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