下面是一种解决方案，您可以设置其中一个图的ylabel并调整它的位置，使其垂直居中。这样可以避免KYC提到的问题。

import numpy as np
import matplotlib.pyplot as plt

def set_shared_ylabel(a, ylabel, labelpad = 0.01):
    """Set a y label shared by multiple axes
    Parameters
    ----------
    a: list of axes
    ylabel: string
    labelpad: float
        Sets the padding between ticklabels and axis label"""

    f = a[0].get_figure()
    f.canvas.draw() #sets f.canvas.renderer needed below

    # get the center position for all plots
    top = a[0].get_position().y1
    bottom = a[-1].get_position().y0

    # get the coordinates of the left side of the tick labels 
    x0 = 1
    for at in a:
        at.set_ylabel('') # just to make sure we don't and up with multiple labels
        bboxes, _ = at.yaxis.get_ticklabel_extents(f.canvas.renderer)
        bboxes = bboxes.inverse_transformed(f.transFigure)
        xt = bboxes.x0
        if xt < x0:
            x0 = xt
    tick_label_left = x0

    # set position of label
    a[-1].set_ylabel(ylabel)
    a[-1].yaxis.set_label_coords(tick_label_left - labelpad,(bottom + top)/2, transform=f.transFigure)

length = 100
x = np.linspace(0,100, length)
y1 = np.random.random(length) * 1000
y2 = np.random.random(length)

f,a = plt.subplots(2, sharex=True, gridspec_kw={'hspace':0})
a[0].plot(x, y1)
a[1].plot(x, y2)
set_shared_ylabel(a, 'shared y label (a. u.)')

Plt.setp()将完成工作:

# plot something
fig, axs = plt.subplots(3,3, figsize=(15, 8), sharex=True, sharey=True)
for i, ax in enumerate(axs.flat):
    ax.scatter(*np.random.normal(size=(2,200)))
    ax.set_title(f'Title {i}')

# set labels
plt.setp(axs[-1, :], xlabel='x axis label')
plt.setp(axs[:, 0], ylabel='y axis label')

您可以创建一个涵盖这两个子图的大子图，然后设置公共标签。

import random
import matplotlib.pyplot as plt

x = range(1, 101)
y1 = [random.randint(1, 100) for _ in range(len(x))]
y2 = [random.randint(1, 100) for _ in range(len(x))]

fig = plt.figure()
ax = fig.add_subplot(111)    # The big subplot
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)

# Turn off axis lines and ticks of the big subplot
ax.spines['top'].set_color('none')
ax.spines['bottom'].set_color('none')
ax.spines['left'].set_color('none')
ax.spines['right'].set_color('none')
ax.tick_params(labelcolor='w', top=False, bottom=False, left=False, right=False)

ax1.loglog(x, y1)
ax2.loglog(x, y2)

# Set common labels
ax.set_xlabel('common xlabel')
ax.set_ylabel('common ylabel')

ax1.set_title('ax1 title')
ax2.set_title('ax2 title')

plt.savefig('common_labels.png', dpi=300)

另一种方法是使用fig.text()直接设置公共标签的位置。

import random
import matplotlib.pyplot as plt

x = range(1, 101)
y1 = [random.randint(1, 100) for _ in range(len(x))]
y2 = [random.randint(1, 100) for _ in range(len(x))]

fig = plt.figure()
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)

ax1.loglog(x, y1)
ax2.loglog(x, y2)

# Set common labels
fig.text(0.5, 0.04, 'common xlabel', ha='center', va='center')
fig.text(0.06, 0.5, 'common ylabel', ha='center', va='center', rotation='vertical')

ax1.set_title('ax1 title')
ax2.set_title('ax2 title')

plt.savefig('common_labels_text.png', dpi=300)

matplotlib 3.4.0新增功能

现在有内置的方法来设置公共轴标签:

supxlabel Fig.supxlabel ('common xlabel ') supylabel fig supylabel('common ylabel ')

要重现OP的日志图(通用标签但独立标题):

x = np.arange(0.01, 10.01, 0.01)
y = 2 ** x

fig, (ax1, ax2) = plt.subplots(2, 1, constrained_layout=True)
ax1.loglog(y, x)
ax2.loglog(x, y)

# separate subplot titles
ax1.set_title('ax1.title')
ax2.set_title('ax2.title')

# common axis labels
fig.supxlabel('fig.supxlabel')
fig.supylabel('fig.supylabel')

你可以在坐标轴上使用set，如下所示:

axes[0].set(xlabel="KartalOl", ylabel="Labeled")

# list loss and acc are your data
fig = plt.figure()
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)

ax1.plot(iteration1, loss)
ax2.plot(iteration2, acc)

ax1.set_title('Training Loss')
ax2.set_title('Training Accuracy')

ax1.set_xlabel('Iteration')
ax1.set_ylabel('Loss')

ax2.set_xlabel('Iteration')
ax2.set_ylabel('Accuracy')